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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluating Performance Portability with the CMS Heterogeneous Pixel Reconstruction code

In the past years the landscape of tools for expressing parallel algorithms in a portable way across various compute accelerators has continued to evolve significantly. There are many technologies on the market that provide portability between CPU, GPUs from several vendors, and in some cases even FPGAs. These technologies include C++ libraries such as Alpaka and Kokkos, compiler directives such as OpenMP, the SYCL open specification that can be implemented as a library or in a compiler, and standard C++ where the compiler is solely responsible for the offloading. Given this developing landscape, users have to choose the technology that best fits their applications and constraints. For example, in the CMS experiment the experience so far in heterogeneous reconstruction algorithms suggests that the full application contains a large number of relatively short computational kernels and memory transfer operations. In this work we use a stand-alone version of the CMS heterogeneous pixel reconstruction code as a realistic use case of HEP reconstruction software that is capable of leveraging GPUs effectively. We summarize the experience of porting this code base from CUDA to Alpaka, Kokkos, SYCL, std::par, and OpenMP offloading. We compare the event processing throughput achieved by each version on NVIDIA and AMD GPUs as well as on a CPU, and compare those to what a native version of the code achieves on each platform.

Andriotis, Nikolaos↗
DOE OSTI2021

UPC++ as_eager Working Group Draft, Revision 2020.6.2

This draft proposes an extension for a new future-based completion variant that can be more effectively streamlined for RMA and atomic access operations that happen to be satisfied at runtime using purely node-local resources. Many such operations are most efficiently performed synchronously using load/store instructions on shared-memory mappings, where the actual access may only require a few CPU instructions. In such cases we believe it’s critical to minimize the overheads imposed by the UPC++ runtime and completion queues, in order to enable efficient operation on hierarchical node hardware using shared-memory bypass. The new upcxx::{source,operation}_cx::as_eager_future() completion variant accomplishes this goal by relaxing the current restriction that future-returning access operations must return a non-ready future whose completion is deferred until a subsequent explicit invocation of user-level progress. This relaxation allows access operations that are completed synchronously to instead return a ready future, thereby avoiding most or all of the runtime costs associated with deferment of future completion and subsequent mandatory entry into the progress engine. We additionally propose to make this new as_eager_future() completion variant the new default completion for communication operations that currently default to returning a future. This should encourage use of the streamlined variant, and may provide performance improvements to some codes without source changes. A mechanism is proposed to restore the legacy behavior on-demand for codes that might happen to rely on deferred completion for correctness. Finally, we propose a new as_eager_promise() completion variant that extends analogous improvements to promise-based completion, and corresponding changes to the default behavior of as_promise().

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Integrating Deep Learning and Hydrodynamic Modeling to Improve the Great Lakes Forecast

The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, trained with the limited data from hypothetical monitoring networks, can provide consistent and robust performance. The LSTM prediction captured the LST spatiotemporal variabilities across the five Great Lakes well, suggesting an effective and efficient way for monitoring network design in assisting the ML-based forecast. Furthermore, we employed an explainable artificial intelligence (XAI) technique named SHapley Additive exPlanations (SHAP) to uncover how the features impact the LSTM prediction. Our XAI analysis shows air temperature is the most influential feature for predicting LST in the trained LSTM. The relatively large bias in the LSTM prediction during the spring and fall was associated with substantial heterogeneity of air temperature during the two seasons. In contrast, the physics-based hydrodynamic model performed better in spring and fall yet exhibited relatively large biases during the summer stratification period. Finally, we developed a statistical integration of the hydrodynamic modeling and deep learning results based on the Best Linear Unbiased Estimator (BLUE). The integration further enhanced prediction accuracy, suggesting its potential for next-generation Great Lakes forecast systems.

Xue, Pengfei (ORCID:000000025702421X)↗
NASA NTRS1993

Fast Multilevel Implementation of Recursive Spectral Bisection for Partitioning Unstructured Problems

If problems involving unstructured meshes are to be solved efficiently on distributed-memory parallel computers, the meshes must be partitioned and distributed across processors in a way that balances tile computational load and minimizes communication. The recursive spectral bisection method (RSB) has been shown to be very effective for such partitioning problems compared to alternative methods, but RSB in its simplest form is expensive. Here a multilevel version of RSB is introduced that attains about an order-of-magnitude improvement in run time on typical examples.

Barnard, Stephen T.↗
NASA NTRS1998

An Adaptable Power System with Software Control Algorithm

A low cost, flexible and modular spacecraft power system design was developed in response to a call for an architecture that could accommodate multiple missions in the small to medium load range. Three upcoming satellites will use this design, with one launch date in 1999 and two in the year 2000. The design consists of modular hardware that can be scaled up or down, without additional cost, to suit missions in the 200 to 600 Watt orbital average load range. The design will be applied to satellite orbits that are circular, polar elliptical and a libration point orbit. Mission unique adaptations are accomplished in software and firmware. In designing this advanced, adaptable power system, the major goals were reduction in weight volume and cost. This power system design represents reductions in weight of 78 percent, volume of 86 percent and cost of 65 percent from previous comparable systems. The efforts to miniaturize the electronics without sacrificing performance has created streamlined power electronics with control functions residing in the system microprocessor. The power system design can handle any battery size up to 50 Amp-hour and any battery technology. The three current implementations will use both nickel cadmium and nickel hydrogen batteries ranging in size from 21 to 50 Amp-hours. Multiple batteries can be used by adding another battery module. Any solar cell technology can be used and various array layouts can be incorporated with no change in Power System Electronics (PSE) hardware. Other features of the design are the standardized interfaces between cards and subsystems and immunity to radiation effects up to 30 krad Total Ionizing Dose (TID) and 35 Mev/cm(exp 2)-kg for Single Event Effects (SEE). The control algorithm for the power system resides in a radiation-hardened microprocessor. A table driven software design allows for flexibility in mission specific requirements. By storing critical power system constants in memory, modifying the system code for other programs is simple. These constants can be altered also by ground command, or in response to an anomolous event. All critical power system functions have backup hardware functions to prevent a software or computer glitch from propagating. A number of battery charge control schemes can be implemented by selecting the proper control terms in the code. The architecture allows the design engineer to tune the system response to various system components and anticipated load profiles without costly alterations. A design trade was made with the size, weight and power dissipation of the electronics versus the performance of the power bus to load variations. Linear, fine control is maintained with a streamlined electronics design. This paper describes the hardware design as well as the software control algorithm. The challenges of closing the system control loop digitally is discussed. Control loop margin and power system performance is presented. Lab measurements are shown and compared to the system response of a hardware model running actual flight software.

Castell, Karen↗
NASA NTRS1996

Computational Nanotechnology at NASA Ames Research Center, 1996

Some forms of nanotechnology appear to have enormous potential to improve aerospace and computer systems; computational nanotechnology, the design and simulation of programmable molecular machines, is crucial to progress. NASA Ames Research Center has begun a computational nanotechnology program including in-house work, external research grants, and grants of supercomputer time. Four goals have been established: (1) Simulate a hypothetical programmable molecular machine replicating itself and building other products. (2) Develop molecular manufacturing CAD (computer aided design) software and use it to design molecular manufacturing systems and products of aerospace interest, including computer components. (3) Characterize nanotechnologically accessible materials of aerospace interest. Such materials may have excellent strength and thermal properties. (4) Collaborate with experimentalists. Current in-house activities include: (1) Development of NanoDesign, software to design and simulate a nanotechnology based on functionalized fullerenes. Early work focuses on gears. (2) A design for high density atomically precise memory. (3) Design of nanotechnology systems based on biology. (4) Characterization of diamonoid mechanosynthetic pathways. (5) Studies of the laplacian of the electronic charge density to understand molecular structure and reactivity. (6) Studies of entropic effects during self-assembly. Characterization of properties of matter for clusters up to sizes exhibiting bulk properties. In addition, the NAS (NASA Advanced Supercomputing) supercomputer division sponsored a workshop on computational molecular nanotechnology on March 4-5, 1996 held at NASA Ames Research Center. Finally, collaborations with Bill Goddard at CalTech, Ralph Merkle at Xerox Parc, Don Brenner at NCSU (North Carolina State University), Tom McKendree at Hughes, and Todd Wipke at UCSC are underway.

Globus, Al↗
DOE OSTI2014

Improving energy efficiency of Embedded DRAM Caches for High-end Computing Systems

With increasing system core-count, the size of last level cache (LLC) has increased and since SRAM consumes high leakage power, power consumption of LLCs is becoming a significant fraction of processor power consumption. To address this, researchers have used embedded DRAM (eDRAM) LLCs which consume low-leakage power. However, eDRAM caches consume a significant amount of energy in the form of refresh energy. In this paper, we propose ESTEEM, an energy saving technique for embedded DRAM caches. ESTEEM uses dynamic cache reconfiguration to turn-off a portion of the cache to save both leakage and refresh energy. It logically divides the cache sets into multiple modules and turns-off possibly different number of ways in each module. Microarchitectural simulations confirm that ESTEEM is effective in improving performance and energy efficiency and provides better results compared to a recently-proposed eDRAM cache energy saving technique, namely Refrint. For single and dual-core simulations, the average saving in memory subsystem (LLC+main memory) on using ESTEEM is 25.8% and 32.6%, respectively and average weighted speedup are 1.09X and 1.22X, respectively. Additional experiments confirm that ESTEEM works well for a wide-range of system parameters.

cache reconfiguration↗
DOE OSTI2013

A Genome-Wide Association Study Suggests Novel Loci Associated with a Schizophrenia-Related Brain-Based Phenotype

Patients with schizophrenia and their siblings typically show subtle changes of brain structures, such as a reduction of hippocampal volume. Hippocampal volume is heritable, may explain a variety of cognitive symptoms of schizophrenia and is thus considered an intermediate phenotype for this mental illness. The aim of our analyses was to identify singlenucleotide polymorphisms (SNP) related to hippocampal volume without making prior assumptions about possible candidate genes. In this study, we combined genetics, imaging and neuropsychological data obtained from the Mind Clinical Imaging Consortium study of schizophrenia (n = 328). A total of 743,591 SNPs were tested for association with hippocampal volume in a genome-wide association study. Gene expression profiles of human hippocampal tissue were investigated for gene regions of significantly associated SNPs. None of the genetic markers reached genome-wide significance. However, six highly correlated SNPs (rs4808611, rs35686037, rs12982178, rs1042178, rs10406920, rs8170) on chromosome 19p13.11, located within or in close proximity to the genes NR2F6, USHBP1, and BABAM1, as well as four SNPs in three other genomic regions (chromosome 1, 2 and 10) had p-values between 6.75610 -6 and 8.3610 -7 . Using existing data of a very recently published GWAS of hippocampal volume and additional data of a multicentre study in a large cohort of adolescents of European ancestry, we found supporting evidence for our results. Furthermore, allelic differences in rs4808611 and rs8170 were highly associated with differential mRNA expression in the cis-acting region. Associations with memory functioning indicate a possible functional importance of the identified risk variants. Our findings provide new insights into the genetic architecture of a brain structure closely linked to schizophrenia. In silico replication, mRNA expression and cognitive data provide additional support for the relevance of our findings. Identification of causal variants and their functional effects may unveil yet unknown players in the neurodevelopment and the pathogenesis of neuropsychiatric disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Wavelet and Deep-Learning-Based Approach for Generation System Problematic Parameters Identification and Calibration

Accurate models of generation systems are critical for maintaining reliable and secure grid operations. In this paper, a novel and systematic approach is proposed to identify and calibrate the generation system problematic parameters using continuous wavelet transform (CWT) and advanced deep-learning technology. The phasor measurement unit (PMU) data are used through “event playback” to check whether the parameter calibration is required, and if yes, a group of suspicious parameters will be identified as the primary problematic parameter candidates (PPCs). These primary PPCs are randomly perturbed to generate the event playback simulation data, which are used by the CWT and convolutional neural networks (CNNs) to further narrow down the primary PPCs into a smaller set of candidates. Then, the identified candidates are perturbed again to generate massive event playback simulation data for training a parameter calibration neural network. Here, we designed a multi-output neural network structure to find the mappings between the perturbed parameters and the simulation data using both CNN and long short-term memory (LSTM) models. Finally, the well-trained and tested CNN-LSTM model is used to estimate the accurate value of the suspicious parameters with actual PMU measurements. The proposed CNN-LSTM network can accurately and reliably estimate the generation-system problematic parameters, and has better performance when compared to other machine-learning methods, such as the multilayer perceptron network and the conditional variational autoencoder method. The accuracy and effectiveness of the proposed approach have been validated through simulation and real-world data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Oxotremorine-M potentiates NMDA receptors by muscarinic receptor dependent and independent mechanisms

Highlights: • The muscarinic receptor agonist oxotremorine-M potentiates NMDA receptors via two different mechanisms. • First, muscarinic M1 receptor activation leads to activation of PKC which phosphorylates and potentiates NMDA receptors. • Second, by a muscarinic receptor-independent mechanism, likely caused by a direct effect of oxotremorine-M on NMDA receptors. • For the latter effect the tri-methyl ammonium moiety of oxotremorine-M is crucial. Muscarinic acetylcholine M1 receptors play an important role in synaptic plasticity in the hippocampus and cortex. Potentiation of NMDA receptors as a consequence of muscarinic acetylcholine M1 receptor activation is a crucial event mediating the cholinergic modulation of synaptic plasticity, which is a cellular mechanism for learning and memory. In Alzheimer's disease, the cholinergic input to the hippocampus and cortex is severely degenerated, and agonists or positive allosteric modulators of M1 receptors are therefore thought to be of potential use to treat the deficits in cognitive functions in Alzheimer's disease. In this study we developed a simple system in which muscarinic modulation of NMDA receptors can be studied in vitro. Human M1 receptors and NR1/2B NMDA receptors were co-expressed in Xenopus oocytes and various muscarinic agonists were assessed for their modulatory effects on NMDA receptor-mediated responses. As expected, NMDA receptor-mediated responses were potentiated by oxotremorine-M, oxotremorine or xanomeline when the drugs were applied between subsequent NMDA responses, an effect which was fully blocked by the muscarinic receptor antagonist atropine. However, in oocytes expressing NR1/2B NMDA receptors but not muscarinic M1 receptors, oxotremorine-M co-applied with NMDA also resulted in a potentiation of NMDA currents and this effect was not blocked by atropine, demonstrating that oxotremorine-M is able to directly potentiate NMDA receptors. Oxotremorine, which is a close analogue of oxotremorine-M, and xanomeline, a chemically distinct muscarinic agonist, did not potentiate NMDA receptors by this direct mechanism. Comparing the chemical structures of the three different muscarinic agonists used in this study suggests that the tri-methyl ammonium moiety present in oxotremorine-M is important for the compound's interaction with NMDA receptors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Association Between Anticholinergic Medication Use and Cognition, Brain Metabolism, and Brain Atrophy in Cognitively Normal Older Adults

Importance of this Paper: The use of anticholinergic (AC) medication is linked to cognitive impairment and an increased risk of dementia. To our knowledge, this is the first study to investigate the association between AC medication use and neuroimaging biomarkers of brain metabolism and atrophy as a proxy for understanding the underlying biology of the clinical effects of AC medications. Objective: To assess the association between AC medication use and cognition, glucose metabolism, and brain atrophy in cognitively normal older adults from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Indiana Memory and Aging Study (IMAS). Design, Setting, and Participants: The ADNI and IMAS are longitudinal studies with cognitive, neuroimaging, and other data collected at regular intervals in clinical and academic research settings. For the participants in the ADNI, visits are repeated 3, 6, and 12 months after the baseline visit and then annually. For the participants in the IMAS, visits are repeated every 18 months after the baseline visit (402 cognitively normal older adults in the ADNI and 49 cognitively normal older adults in the IMAS were included in the present analysis). Participants were either taking (hereafter referred to as the AC + participants [52 from the ADNI and 8 from the IMAS]) or not taking (hereafter referred to as the AC - participants [350 from the ADNI and 41 from the IMAS]) at least 1 medication with medium or high AC activity. Data analysis for this study was performed in November 2015. Main Outcomes and Measures: Cognitive scores, mean fludeoxyglucose F 18 standardized uptake value ratio (participants from the ADNI only), and brain atrophy measures from structural magnetic resonance imaging were compared between AC + participants and AC - participants after adjusting for potential confounders. The total AC burden score was calculated and was related to target measures. The association of AC use and longitudinal clinical decline (mean [SD] follow-up period, 32.1 [24.7] months [range, 6-108 months]) was examined using Cox regression. Results: The 52 AC + participants (mean [SD] age, 73.3 [6.6] years) from the ADNI showed lower mean scores on Weschler Memory Scale–Revised Logical Memory Immediate Recall (raw mean scores: 13.27 for AC + participants and 14.16 for AC - participants; P = .04) and the Trail Making Test Part B (raw mean scores: 97.85 seconds for AC + participants and 82.61 seconds for AC - participants; P = .04) and a lower executive function composite score (raw mean scores: 0.58 for AC + participants and 0.78 for AC - participants; P = .04) than the 350 AC - participants (mean [SD] age, 73.3 [5.8] years) from the ADNI. Reduced total cortical volume and temporal lobe cortical thickness and greater lateral ventricle and inferior lateral ventricle volumes were seen in the AC + participants relative to the AC - participants. Conclusions and Relevance of this Paper: The use of AC medication was associated with increased brain atrophy and dysfunction and clinical decline. Thus and finally, use of AC medication among older adults should likely be discouraged if alternative therapies are available.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Composite WO 3 /TiO 2 nanostructures for high electrochromic activity

A composite material consisting of TiO 2 nanotubes (NT) with WO 3 electrodeposited on its surface has been fabricated, detached from its Ti substrate, and attached to a fluorine-doped tin oxide (FTO) film on glass for application to electrochromic (EC) reactions. Several adhesion layers were tested, finding that a paste of TiO 2 made from commercially available TiO 2 nanoparticles creates an interface for the TiO 2 NT film to attach to the FTO glass, which is conductive and does not cause solution-phase ions in an electrolyte to bind irreversibly with the material. The effect of NT length and WO 3 concentration on the EC performance were studied. As a result, the composite WO 3 /TiO 2 nanostructures showed higher ion storage capacity, better stability, enhanced EC contrast, and longer memory time compared with the pure WO 3 and TiO 2 materials

36 MATERIALS SCIENCE↗
DOE OSTI2015

Proposal for a graphene-based all-spin logic gate

In this work, we present a graphene-based all-spin logic gate (G-ASLG) that integrates the functionalities of perpendicular anisotropy magnetic tunnel junctions (p-MTJs) with spin transport in graphene-channel. It provides an ideal integration of logic and memory. The input and output states are defined as the relative magnetization between free layer and fixed layer of p-MTJs. They can be probed by the tunnel magnetoresistance and controlled by spin transfer torque effect. Using lateral non-local spin valve, the spin information is transmitted by the spin-current interaction through graphene channels. By using a physics-based spin current compact model, the operation of G-ASLG is demonstrated and its performance is analyzed. It allows us to evaluate the influence of parameters, such as spin injection efficiency, spin diffusion length, contact area, the device length, and their interdependence, and to optimize the energy and dynamic performance. Compared to other beyond-CMOS solutions, longer spin information transport length (∼μm), higher data throughput, faster computing speed (∼ns), and lower power consumption (∼μA) can be expected from the G-ASLG.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Quantum dynamics of a molecular emitter strongly coupled with surface plasmon polaritons: A macroscopic quantum electrodynamics approach

In this work, we study a molecular emitter above a silver surface in the framework of macroscopic quantum electrodynamics and explore the population dynamics including non-Markovian effects. The theory we present is general for molecular fluorescence in the presence of dielectrics with any space-dependent, frequency-dependent, or complex dielectric functions. Furthermore, the proposed theory allows us to calculate the memory kernel of polaritons using computational electrodynamics packages. In the limit of a high vibration frequency, the different strengths of exciton-polariton couplings lead to distinct characteristics in the population dynamics, e.g., Franck-Condon-Rabi oscillation. (The frequency of Rabi oscillation is dependent on the Franck-Condon factor.) Additionally, in a specific condition, we derive a parameter-free formula that can be used to estimate the exciton-polariton coupling between a molecular emitter and a nanocavity, and the coupling estimated by our theory is in good agreement with the reported experimental results.

Surface plasmon polaritons↗
DOE OSTI2014

A new online detector for estimation of peripheral neutron equivalent dose in organ

Purpose: Peripheral dose in radiotherapy treatments represents a potential source of secondary neoplasic processes. As in the last few years, there has been a fast-growing concern on neutron collateral effects, this work focuses on this component. A previous established methodology to estimate peripheral neutron equivalent doses relied on passive (TLD, CR39) neutron detectors exposed in-phantom, in parallel to an active [static random access memory (SRAMnd)] thermal neutron detector exposed ex-phantom. A newly miniaturized, quick, and reliable active thermal neutron detector (TNRD, Thermal Neutron Rate Detector) was validated for both procedures. This first miniaturized active system eliminates the long postprocessing, required for passive detectors, giving thermal neutron fluences in real time. Methods: To validate TNRD for the established methodology, intrinsic characteristics, characterization of 4 facilities [to correlate monitor value (MU) with risk], and a cohort of 200 real patients (for second cancer risk estimates) were evaluated and compared with the well-established SRAMnd device. Finally, TNRD was compared to TLD pairs for 3 generic radiotherapy treatments through 16 strategic points inside an anthropomorphic phantom. Results: The performed tests indicate similar linear dependence with dose for both detectors, TNRD and SRAMnd, while a slightly better reproducibility has been obtained for TNRD (1.7% vs 2.2%). Risk estimates when delivering 1000 MU are in good agreement between both detectors (mean deviation of TNRD measurements with respect to the ones of SRAMnd is 0.07 cases per 1000, with differences always smaller than 0.08 cases per 1000). As far as the in-phantom measurements are concerned, a mean deviation smaller than 1.7% was obtained. Conclusions: The results obtained indicate that direct evaluation of equivalent dose estimation in organs, both in phantom and patients, is perfectly feasible with this new detector. This will open the door to an easy implementation of specific peripheral neutron dose models for any type of treatment and facility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Two new SciDAC institutes promote mathematical tools and software technology for high-performance computing

Bigger is often said to be better, and the newest extreme-scale computers certainly are bigger, with millions of processing units. Moreover, the breadth of science performed on the U.S. Department of Energy (DOE) computing facilities is expanding, with new technology such as artificial intelligence emerging. These advances are exciting, creating new opportunities for scientific discovery; however, they also raise new questions for scientists who want to exploit these advances for tackling more complex problems. Will my simulation code be able to utilize the accelerators in extreme-scale computing systems? Can I take advantage of the deepening memory hierarchy in heterogeneous processors? Is there a way around bottlenecks caused by the widening ratio of peak floating-point operations per second to I/0 bandwidth? How can I manage my huge amounts of data effectively? Can I analyze data in situ, or must I transfer it to offline storage for later analysis? To address such questions, DOE announced that it is providing $57.5 million over the next five years for two multidisciplinary teams — FASTMath and RAPIDS2 — to develop new tools and techniques to harness supercomputers for scientific discovery. The teams, called SciDAC Institutes, are part of the Scientific Discovery through Advanced Computing program.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Measuring software technology

Results are reported from a series of investigations into the effectiveness of various methods and tools used in a software production environment. The basis for the analysis is a project data base, built through extensive data collection and process instrumentation. The project profiles become an organizational memory, serving as a reference point for an active program of measurement and experimentation on software technology.

Agresti, W. W.↗
NASA NTRS1992

Hypercluster Parallel Processor

Hypercluster computer system includes multiple digital processors, operation of which coordinated through specialized software. Configurable according to various parallel-computing architectures of shared-memory or distributed-memory class, including scalar computer, vector computer, reduced-instruction-set computer, and complex-instruction-set computer. Designed as flexible, relatively inexpensive system that provides single programming and operating environment within which one can investigate effects of various parallel-computing architectures and combinations on performance in solution of complicated problems like those of three-dimensional flows in turbomachines. Hypercluster software and architectural concepts are in public domain.

Blech, Richard A.↗